As enterprises accumulate ever greater amounts of data on their transactions, processes, products, and operations, online analytical processing has become an essential part of doing business. The number of tools and techniques addressing analytical processing has grown, enabling data analysts to quickly analyze and navigate through vast complex collections of data.
By conventional practice, online analytical processing is traditionally performed on data that is separate from live transactional data. Further, joins, unions, and calculations are typically performed on data retrieved from a database. So, if a user wishes to combine views, complicated modifications to the analytical software are often required. Accordingly, although current approaches provide a wide variety of functionality, there is room for improvement.